ε
LDP Showcase
Correction EstimatorGitLabDocs

All demos

Direct links to every scenario and mechanism page we've built.

Scenarios

Healthcare scenario

Satisfaction ratings, symptom severity, wait times. Pre-anonymized + on-the-fly + insert flows.

GRRM · Laplace · Gaussian

Financial scenario

Spending categories, brackets, transaction types. Also hosts the amount-mean real-vs-integer comparison.

GRRM · Laplace · Gaussian

Telemetry scenario

Feature usage, session duration, platform analytics.

GRRM · Laplace · Gaussian

Survey scenario

Political leaning, income, education, age group.

GRRM · Laplace · Gaussian

Mechanism deep dives

Correction estimator

Unbiased frequency recovery from LDP-perturbed histograms. Single-value estimate, full-distribution, and mean-from-frequencies.

GRRM (closed form) · Laplace (matrix inv.)

Laplace mean: real vs integer

Same data, same ε, two units. Apply Laplace per row then average — see how the continuous mean and the bucket-index mean compare.

anon.ldp_laplace_real · anon.ldp_laplace

One-hot vs scalar histogram

Two ways to estimate a histogram under Laplace/Gaussian LDP: scalar + correction, vs one-hot vector + noise + sum. Shows where OHE wins.

anon.ldp_{laplace,gaussian}_onehot

Exponential mechanism (central DP)

Pick the most common symptom-severity level under ε-DP. Run 1000 trials and plot how often the mechanism selects each candidate.

anon.ldp_exponential_mode (utility = count)